
import numpy as np
import pandas as pd
pd.set_option('display.max_columns', 40)
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import seaborn as sns
%matplotlib inline
sns.set_style('darkgrid')
import plotly.express as px
from sklearn.cluster import KMeans
import warnings
warnings.filterwarnings('ignore');


df=pd.read_csv(r"C:/Users/home/Documents/Microsoft Engage Project/cars_details_2022.csv")


df.head(10)


df.Make.unique()

array(['Tata', 'Datsun', 'Renault', 'Maruti Suzuki', 'Hyundai', 'Premier',
       'Toyota', 'Nissan', 'Volkswagen', 'Ford', 'Mahindra', 'Fiat',
       'Honda', 'Jeep', 'Isuzu', 'Skoda', 'Audi', nan, 'Dc', 'Mini',
       'Volvo', 'Jaguar', 'Bmw', 'Land Rover', 'Porsche', 'Lexus',
       'Maserati', 'Lamborghini', 'Bentley', 'Ferrari', 'Aston Martin',
       'Bugatti', 'Bajaj', 'Icml', 'Force', 'Mg', 'Kia',
       'Land Rover Rover', 'Mitsubishi', 'Maruti Suzuki R'], dtype=object)


df.columns

Index(['Unnamed: 0', 'Make', 'Model', 'Variant', 'Ex-Showroom_Price',
       'Displacement', 'Cylinders', 'Valves_Per_Cylinder', 'Drivetrain',
       'Cylinder_Configuration',
       ...
       'Leather_Wrapped_Steering', 'Automatic_Headlamps', 'Engine_Type',
       'ASR_/_Traction_Control', 'Cruise_Control', 'USB_Ports',
       'Heads-Up_Display', 'Welcome_Lights', 'Battery', 'Electric_Range'],
      dtype='object', length=141)


df.shape

(1276, 141)


df.isnull().sum()

Unnamed: 0              0
Make                   75
Model                   0
Variant                 0
Ex-Showroom_Price       0
                     ... 
USB_Ports            1247
Heads-Up_Display     1225
Welcome_Lights       1207
Battery              1263
Electric_Range       1259
Length: 141, dtype: int64


df.info

<bound method DataFrame.info of       Unnamed: 0        Make      Model        Variant Ex-Showroom_Price  \
0              0        Tata  Nano Genx             Xt      Rs. 2,92,667   
1              1        Tata  Nano Genx             Xe      Rs. 2,36,447   
2              2        Tata  Nano Genx        Emax Xm      Rs. 2,96,661   
3              3        Tata  Nano Genx            Xta      Rs. 3,34,768   
4              4        Tata  Nano Genx             Xm      Rs. 2,72,223   
...          ...         ...        ...            ...               ...   
1271        1271       Honda       City   Vx Mt Diesel     Rs. 13,02,000   
1272        1272       Honda       City   Zx Mt Diesel     Rs. 14,21,000   
1273        1273       Honda       City  Zx Cvt Petrol     Rs. 14,31,000   
1274        1274       Honda       City   V Cvt Petrol     Rs. 12,01,000   
1275        1275  Mitsubishi    Montero         3.2 At     Rs. 68,62,560   

     Displacement  Cylinders  Valves_Per_Cylinder               Drivetrain  \
0          624 cc        2.0                  2.0   RWD (Rear Wheel Drive)   
1          624 cc        2.0                  2.0   RWD (Rear Wheel Drive)   
2          624 cc        2.0                  2.0   RWD (Rear Wheel Drive)   
3          624 cc        2.0                  2.0   RWD (Rear Wheel Drive)   
4          624 cc        2.0                  2.0   RWD (Rear Wheel Drive)   
...           ...        ...                  ...                      ...   
1271      1498 cc        4.0                  4.0  FWD (Front Wheel Drive)   
1272      1498 cc        4.0                  4.0  FWD (Front Wheel Drive)   
1273      1497 cc        4.0                  4.0  FWD (Front Wheel Drive)   
1274      1497 cc        4.0                  4.0  FWD (Front Wheel Drive)   
1275      3200 cc        4.0                  4.0    AWD (All Wheel Drive)   

     Cylinder_Configuration Emission_Norm      Engine_Location Fuel_System  \
0                   In-line         BS IV     Rear, Transverse   Injection   
1                   In-line         BS IV     Rear, Transverse   Injection   
2                   In-line         BS IV     Rear, Transverse   Injection   
3                   In-line         BS IV     Rear, Transverse   Injection   
4                   In-line         BS IV     Rear, Transverse   Injection   
...                     ...           ...                  ...         ...   
1271                In-line         BS IV    Front, Transverse   Injection   
1272                In-line         BS IV    Front, Transverse   Injection   
1273                In-line          BS 6    Front, Transverse   Injection   
1274                In-line          BS 6    Front, Transverse   Injection   
1275                In-line         BS IV  Front, Longitudinal   Injection   

     Fuel_Tank_Capacity Fuel_Type   Height   Length    Width  Body_Type  \
0             24 litres    Petrol  1652 mm  3164 mm  1750 mm  Hatchback   
1             24 litres    Petrol  1652 mm  3164 mm  1750 mm  Hatchback   
2             15 litres       CNG  1652 mm  3164 mm  1750 mm  Hatchback   
3             24 litres    Petrol  1652 mm  3164 mm  1750 mm  Hatchback   
4             24 litres    Petrol  1652 mm  3164 mm  1750 mm  Hatchback   
...                 ...       ...      ...      ...      ...        ...   
1271          40 litres    Diesel  1495 mm  4440 mm  1695 mm      Sedan   
1272          40 litres    Diesel  1495 mm  4440 mm  1695 mm      Sedan   
1273          40 litres    Petrol  1495 mm  4440 mm  1695 mm      Sedan   
1274          40 litres    Petrol  1495 mm  4440 mm  1695 mm      Sedan   
1275          88 litres    Diesel  1900 mm  4900 mm  1875 mm        SUV   

      Doors  ... Rear_Center_Armrest iPod_Compatibility  \
0       5.0  ...                 NaN                NaN   
1       5.0  ...                 NaN                NaN   
2       4.0  ...                 NaN                NaN   
3       5.0  ...                 NaN                NaN   
4       5.0  ...                 NaN                NaN   
...     ...  ...                 ...                ...   
1271    4.0  ...         Cup Holders                Yes   
1272    4.0  ...         Cup Holders                Yes   
1273    4.0  ...         Cup Holders                Yes   
1274    4.0  ...         Cup Holders                Yes   
1275    5.0  ...         Cup Holders                Yes   

     ESP_(Electronic_Stability_Program) Cooled_Glove_Box  \
0                                   NaN              NaN   
1                                   NaN              NaN   
2                                   NaN              NaN   
3                                   NaN              NaN   
4                                   NaN              NaN   
...                                 ...              ...   
1271                                NaN              NaN   
1272                                NaN              Yes   
1273                                NaN              NaN   
1274                                NaN              NaN   
1275                                Yes              Yes   

     Recommended_Tyre_Pressure Heated_Seats Turbocharger  \
0                          NaN          NaN          NaN   
1                          NaN          NaN          NaN   
2                          NaN          NaN          NaN   
3                          NaN          NaN          NaN   
4                          NaN          NaN          NaN   
...                        ...          ...          ...   
1271                       NaN          NaN          Yes   
1272                       NaN          NaN          Yes   
1273                       NaN          NaN          NaN   
1274                       NaN          NaN          NaN   
1275                       NaN   Only front          Yes   

     ISOFIX_(Child-Seat_Mount) Rain_Sensing_Wipers Paddle_Shifters  \
0                          NaN                 NaN             NaN   
1                          NaN                 NaN             NaN   
2                          NaN                 NaN             NaN   
3                          NaN                 NaN             NaN   
4                          NaN                 NaN             NaN   
...                        ...                 ...             ...   
1271                       Yes                 NaN             NaN   
1272                       Yes                 Yes             NaN   
1273                       Yes                 NaN             Yes   
1274                       Yes                 NaN             Yes   
1275                       Yes                 Yes             NaN   

     Leather_Wrapped_Steering Automatic_Headlamps Engine_Type  \
0                         NaN                 NaN         NaN   
1                         NaN                 NaN         NaN   
2                         NaN                 NaN         NaN   
3                         NaN                 NaN         NaN   
4                         NaN                 NaN         NaN   
...                       ...                 ...         ...   
1271                      Yes                 NaN         NaN   
1272                      Yes                 Yes         NaN   
1273                      Yes                 Yes         NaN   
1274                      NaN                 NaN         NaN   
1275                      Yes                 NaN         NaN   

     ASR_/_Traction_Control Cruise_Control USB_Ports Heads-Up_Display  \
0                       NaN            NaN       NaN              NaN   
1                       NaN            NaN       NaN              NaN   
2                       NaN            NaN       NaN              NaN   
3                       NaN            NaN       NaN              NaN   
4                       NaN            NaN       NaN              NaN   
...                     ...            ...       ...              ...   
1271                    NaN            Yes       NaN              NaN   
1272                    NaN            Yes       NaN              NaN   
1273                    NaN            Yes       NaN              NaN   
1274                    NaN            Yes       NaN              NaN   
1275                    Yes            Yes       NaN              NaN   

     Welcome_Lights Battery Electric_Range  
0               NaN     NaN            NaN  
1               NaN     NaN            NaN  
2               NaN     NaN            NaN  
3               NaN     NaN            NaN  
4               NaN     NaN            NaN  
...             ...     ...            ...  
1271            NaN     NaN            NaN  
1272            NaN     NaN            NaN  
1273            NaN     NaN            NaN  
1274            NaN     NaN            NaN  
1275            NaN     NaN            NaN  

[1276 rows x 141 columns]>


df.describe().T


l_D = len(df)
c_m = len(df.Make.unique())
c_c = len(df.Model.unique())
n_f = len(df.columns)
fig = px.bar(x=['Observations',"Makers",'Models','Features'],y=[l_D,c_m,c_c,n_f], width=800,height=400)
fig.update_layout(
    title="Dataset Statistics",
    xaxis_title="",
    yaxis_title="Counts",
    font=dict(
        size=16,
    )
)

fig.show()


df['car'] = df.Make + ' ' + df.Model
c = ['Make','Model','car','Variant','Body_Type','Fuel_Type','Fuel_System','Type','Drivetrain','Ex-Showroom_Price','Displacement','Cylinders',
     'ARAI_Certified_Mileage','Power','Torque','Fuel_Tank_Capacity','Height','Length','Width','Doors','Seating_Capacity','Wheelbase','Number_of_Airbags']
df_full = df.copy()
df['Ex-Showroom_Price'] = df['Ex-Showroom_Price'].str.replace('Rs. ','',regex=False)
df['Ex-Showroom_Price'] = df['Ex-Showroom_Price'].str.replace(',','',regex=False)
df['Ex-Showroom_Price'] = df['Ex-Showroom_Price'].astype(int)
df = df[c]
df = df[~df.ARAI_Certified_Mileage.isnull()]
df = df[~df.Make.isnull()]
df = df[~df.Width.isnull()]
df = df[~df.Cylinders.isnull()]
df = df[~df.Wheelbase.isnull()]
df = df[~df['Fuel_Tank_Capacity'].isnull()]
df = df[~df['Seating_Capacity'].isnull()]
df = df[~df['Torque'].isnull()]
df['Height'] = df['Height'].str.replace(' mm','',regex=False).astype(float)
df['Length'] = df['Length'].str.replace(' mm','',regex=False).astype(float)
df['Width'] = df['Width'].str.replace(' mm','',regex=False).astype(float)
df['Wheelbase'] = df['Wheelbase'].str.replace(' mm','',regex=False).astype(float)
df['Fuel_Tank_Capacity'] = df['Fuel_Tank_Capacity'].str.replace(' litres','',regex=False).astype(float)
df['Displacement'] = df['Displacement'].str.replace(' cc','',regex=False)
df.loc[df.ARAI_Certified_Mileage == '9.8-10.0 km/litre','ARAI_Certified_Mileage'] = '10'
df.loc[df.ARAI_Certified_Mileage == '10kmpl km/litre','ARAI_Certified_Mileage'] = '10'
df['ARAI_Certified_Mileage'] = df['ARAI_Certified_Mileage'].str.replace(' km/litre','',regex=False).astype(float)
df.Number_of_Airbags.fillna(0,inplace= True)
df['price'] = df['Ex-Showroom_Price'] * 0.014
df.drop(columns='Ex-Showroom_Price', inplace= True)
df.price = df.price.astype(int)
HP = df.Power.str.extract(r'(\d{1,4}).*').astype(int) * 0.98632
HP = HP.apply(lambda x: round(x,2))
TQ = df.Torque.str.extract(r'(\d{1,4}).*').astype(int)
TQ = TQ.apply(lambda x: round(x,2))
df.Torque = TQ
df.Power = HP
df.Doors = df.Doors.astype(int)
df.Seating_Capacity = df.Seating_Capacity.astype(int)
df.Number_of_Airbags = df.Number_of_Airbags.astype(int)
df.Displacement = df.Displacement.astype(int)
df.Cylinders = df.Cylinders.astype(int)
df.columns = ['make', 'model','car', 'variant', 'body_type', 'fuel_type', 'fuel_system','type', 'drivetrain', 'displacement', 'cylinders',
              'mileage', 'power', 'torque', 'fuel_tank','height', 'length', 'width', 'doors', 'seats', 'wheelbase','airbags', 'price']


df.tail(10)


df.isnull().sum()

make            0
model           0
car             0
variant         0
body_type       0
fuel_type       0
fuel_system     1
type            0
drivetrain      1
displacement    0
cylinders       0
mileage         0
power           0
torque          0
fuel_tank       0
height          0
length          0
width           0
doors           0
seats           0
wheelbase       0
airbags         0
price           0
dtype: int64


df.describe().T


df[df.model =='Corolla Altis']


fig,(ax1,ax2) = plt.subplots(2,1,figsize=(14,11))
sns.histplot(data=df, x='price',bins=50, alpha=.6, color='darkblue', ax=ax1)
ax12 = ax1.twinx()
sns.kdeplot(data=df, x='price', alpha=.2,fill= True,color="#254b7f",ax=ax12,linewidth=0)
ax12.grid()
ax1.set_title('Histogram of cars price data',fontsize=16)
ax1.set_xlabel('')
logbins = np.logspace(np.log10(3000),np.log10(744944.578),50)
sns.histplot(data=df, x='price',bins=logbins,alpha=.6, color='darkblue',ax=ax2)
ax2.set_title('Histogram of cars price data (log scale)',fontsize=16)
ax2.set_xscale('log')
ax22 = ax2.twinx()
ax22.grid()
sns.kdeplot(data=df, x='price', alpha=.2,fill= True,color="#254b7f",ax=ax22,log_scale=True,linewidth=0)
ax2.set_xlabel('Price (log)', fontsize=14)
ax22.set_xticks((800,1000,10000,100000,1000000))
ax2.xaxis.set_tick_params(labelsize=14);
ax1.xaxis.set_tick_params(labelsize=14);


plt.figure(figsize=(12,6))
sns.boxplot(data=df, x='price',width=.3,color='blue', hue= 'fuel_type')
plt.title('Box plot of Price',fontsize=18)
plt.xticks([i for i in range(0,800000,100000)],[f'{i:,}$' for i in range(0,800000,100000)],fontsize=14)
plt.xlabel('price',fontsize=14);


plt.figure(figsize=(16,7))
sns.countplot(data=df, y='body_type',alpha=.6,color='darkblue')
plt.title('Cars by car body type',fontsize=20)
plt.xticks(fontsize=14)
plt.yticks(fontsize=14)
plt.xlabel('')
plt.ylabel('');


plt.figure(figsize=(12,6))
sns.boxplot(data=df, x='price', y='body_type', palette='viridis')
plt.title('Box plot of Price of every body type',fontsize=18)
plt.ylabel('')
plt.yticks(fontsize=14)
plt.xticks([i for i in range(0,800000,100000)],[f'{i:,}$' for i in range(0,800000,100000)],fontsize=14);


plt.figure(figsize=(11,6))
sns.countplot(data=df, x='fuel_type',alpha=.6, color='darkblue')
plt.title('Cars count by engine fuel type',fontsize=18)
plt.xlabel('Fuel Type', fontsize=16)
plt.xticks(fontsize=14)
plt.yticks(fontsize=14)
plt.ylabel('');


plt.figure(figsize=(14,6))
sns.histplot(data=df, x='displacement',alpha=.6, color='darkblue',bins=10)
plt.title('Cars by engine size (in CC)',fontsize=18)
plt.xticks(fontsize=13);
plt.yticks(fontsize=13);


plt.figure(figsize=(14,6))
sns.histplot(data=df, x='power',alpha=.6, color='darkblue')
plt.title('Cars by engine size (in CC)',fontsize=18);
plt.xticks(fontsize=13);
plt.yticks(fontsize=13);


plt.figure(figsize=(10,8))
sns.scatterplot(data=df, x='power', y='price',hue='body_type',palette='viridis',alpha=.89, s=120 );
plt.xticks(fontsize=13);
plt.yticks(fontsize=13)
plt.xlabel('power',fontsize=14)
plt.ylabel('price',fontsize=14)
plt.title('Relation between power and price',fontsize=20);


plt.figure(figsize=(10,8))
ax= fig.add_subplot()
sns.jointplot(data=df, x='mileage', y='price',kind= 'reg',ax=ax, palette='viridis',height=8,  ratio=7)
ax.text(.5,.7,'Relation between Power and price', fontsize=18)
ax.set_xlabel('Power (HP)', fontsize= 15);

<Figure size 720x576 with 0 Axes>


plt.figure(figsize=(22,8))
sns.heatmap(df.corr(), annot=True, fmt='.2%')
plt.title('Correlation between differet variable',fontsize=20)
plt.xticks(fontsize=14, rotation=320)
plt.yticks(fontsize=14);


sns.pairplot(df,vars=[ 'displacement', 'mileage', 'power', 'price'], hue= 'fuel_type',
             palette=sns.color_palette('magma',n_colors=4),diag_kind='kde',height=2, aspect=1.8);


fig = px.scatter_3d(df, x='power', z='price', y='mileage',color='make',width=800,height=750)
fig.update_layout(showlegend=True)
fig.show();

	count	mean	std	min	25%	50%	75%	max
Unnamed: 0	1276.0	637.500000	368.493781	0.0	318.75	637.5	956.25	1275.0
Cylinders	1210.0	4.380992	1.660957	2.0	4.00	4.0	4.00	16.0
Valves_Per_Cylinder	1174.0	3.977853	0.833763	1.0	4.00	4.0	4.00	16.0
Doors	1272.0	4.550314	0.747816	2.0	4.00	5.0	5.00	5.0
Seating_Capacity	1270.0	5.270079	1.145231	2.0	5.00	5.0	5.00	16.0
Number_of_Airbags	1141.0	3.787029	2.522399	1.0	2.00	2.0	6.00	14.0
USB_Ports	29.0	1.793103	0.773642	1.0	1.00	2.0	2.00	3.0

	count	mean	std	min	25%	50%	75%	max
displacement	987.0	1759.184397	924.993708	624.000	1198.00	1496.00	1988.00	6752.00
cylinders	987.0	4.220871	1.380041	2.000	4.00	4.00	4.00	12.00
mileage	987.0	18.515380	4.588321	3.400	16.00	18.49	21.70	28.40
power	987.0	141.617224	116.238232	33.530	81.86	102.58	152.88	778.21
torque	987.0	244.030395	162.614837	10.000	120.00	200.00	320.00	1712.00
fuel_tank	987.0	50.920871	15.318039	24.000	40.00	45.00	60.00	105.00
height	987.0	1583.807340	152.821356	1.845	1495.00	1549.00	1655.00	2055.00
length	987.0	4252.248875	447.163835	4.640	3985.00	4315.00	4568.00	5575.00
width	987.0	1775.582416	144.234947	1.845	1695.00	1745.00	1832.00	2226.00
doors	987.0	4.570415	0.714850	2.000	4.00	5.00	5.00	5.00
seats	987.0	5.266464	1.085082	2.000	5.00	5.00	5.00	9.00
wheelbase	987.0	2606.583587	180.699575	1840.000	2470.00	2590.00	2700.00	3266.00
airbags	987.0	3.175279	2.500847	0.000	2.00	2.00	6.00	14.00
price	987.0	48009.175279	105460.579796	3310.000	10104.50	13994.00	27626.50	744944.00

	make	model	car	variant	body_type	fuel_type	fuel_system	type	drivetrain	displacement	cylinders	mileage	power	torque	fuel_tank	height	length	width	doors	seats	wheelbase	airbags	price
734	Toyota	Corolla Altis	Toyota Corolla Altis	G Petrol	Sedan	Petrol	Injection	Manual	FWD (Front Wheel Drive)	1798	4	16.7	138.08	173	55.0	1475.0	4620.0	1775.0	4	5	2700.0	3	23030
735	Toyota	Corolla Altis	Toyota Corolla Altis	G At Petrol	Sedan	Petrol	Injection	Automatic	FWD (Front Wheel Drive)	1798	4	16.7	138.08	173	55.0	1475.0	4620.0	1775.0	4	5	2700.0	3	25284
736	Toyota	Corolla Altis	Toyota Corolla Altis	Gl Petrol	Sedan	Petrol	Injection	Manual	FWD (Front Wheel Drive)	1798	4	16.7	138.08	173	55.0	1475.0	4620.0	1775.0	4	5	2700.0	7	26348
737	Toyota	Corolla Altis	Toyota Corolla Altis	Gl Diesel	Sedan	Diesel	Injection	Manual	FWD (Front Wheel Drive)	1364	4	21.0	86.80	205	43.0	1475.0	4620.0	1775.0	4	5	2700.0	3	27104
738	Toyota	Corolla Altis	Toyota Corolla Altis	G Diesel	Sedan	Diesel	Injection	Manual	FWD (Front Wheel Drive)	1364	4	21.0	86.80	205	43.0	1475.0	4620.0	1775.0	4	5	2700.0	3	24794
739	Toyota	Corolla Altis	Toyota Corolla Altis	Vl At Petrol	Sedan	Petrol	Injection	Automatic	FWD (Front Wheel Drive)	1798	4	16.7	138.08	173	55.0	1475.0	4620.0	1775.0	4	5	2700.0	7	28266

UNDERSTANDING THE DATA¶

Here we can observe that there are so many null values in the last columns which can provide a problem while analyzing the data, so we have to clean the dataset to make accurate analysis and provide proper solution.¶

CLEANING THE DATA¶

ANALYSIS OF THE DATA¶

Now let us check the distribution of some features in the dataset,¶

Firstly let us Check the price distribution, we will use both normal and log scales due to the huge difference in the prices¶

SUV's Sedans and hatchbacks seems to be the dominating car types¶

Analyzing the relationship between different entities in the dataset:-¶

It's Clear that Car body type strongly affect the price and are corelated with each other¶

> Now let us check cars by Fuel type¶

From the above data we can observe that most of the cars seems to be run on Petrol or Diesel¶

> Now let us check the cars by engine size¶

From the above plot we can observe that most of cars have engine size in the 1000:2000cc range¶

> Now let us check the Horsepower of cars:-¶

> Then we check the relation horsepower and price considering diffreent body type¶

From the above scatterplot we can say that:-¶

> Now let us also look into the relation between Mileage and price¶

From the above plots we can conclude that expensive cars tend to have worse mileage¶

> We can also check the overall correlation between variables with each other¶

For this we make a pearson correlation grid¶

The above heatmap shows the corelation between different variables in the dataset.¶

>Now we check an extensive scatter plot grid of more numerical variable to investigate the realtion in more detail¶

> Now lets make a 3D scatter plot to check for obvious clusters with main features as price horsepower and mileage¶

Now let us more interactive plot to show the previous plot and also adding the car manufacturer¶

The above plot is a 3D Scatter plot of different Car models¶

This is how the Automotive Industry could harness data to take informed decisions.¶

	Unnamed: 0	Make	Model	Variant	Ex-Showroom_Price	Displacement	Cylinders	Valves_Per_Cylinder	Drivetrain	Cylinder_Configuration	Emission_Norm	Engine_Location	Fuel_System	Fuel_Tank_Capacity	Fuel_Type	Height	Length	Width	Body_Type	Doors	...	Rear_Center_Armrest	iPod_Compatibility	ESP_(Electronic_Stability_Program)	Cooled_Glove_Box	Recommended_Tyre_Pressure	Heated_Seats	Turbocharger	ISOFIX_(Child-Seat_Mount)	Rain_Sensing_Wipers	Paddle_Shifters	Leather_Wrapped_Steering	Automatic_Headlamps	Engine_Type	ASR_/_Traction_Control	Cruise_Control	USB_Ports	Heads-Up_Display	Welcome_Lights	Battery	Electric_Range
0	0	Tata	Nano Genx	Xt	Rs. 2,92,667	624 cc	2.0	2.0	RWD (Rear Wheel Drive)	In-line	BS IV	Rear, Transverse	Injection	24 litres	Petrol	1652 mm	3164 mm	1750 mm	Hatchback	5.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	1	Tata	Nano Genx	Xe	Rs. 2,36,447	624 cc	2.0	2.0	RWD (Rear Wheel Drive)	In-line	BS IV	Rear, Transverse	Injection	24 litres	Petrol	1652 mm	3164 mm	1750 mm	Hatchback	5.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	2	Tata	Nano Genx	Emax Xm	Rs. 2,96,661	624 cc	2.0	2.0	RWD (Rear Wheel Drive)	In-line	BS IV	Rear, Transverse	Injection	15 litres	CNG	1652 mm	3164 mm	1750 mm	Hatchback	4.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
3	3	Tata	Nano Genx	Xta	Rs. 3,34,768	624 cc	2.0	2.0	RWD (Rear Wheel Drive)	In-line	BS IV	Rear, Transverse	Injection	24 litres	Petrol	1652 mm	3164 mm	1750 mm	Hatchback	5.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
4	4	Tata	Nano Genx	Xm	Rs. 2,72,223	624 cc	2.0	2.0	RWD (Rear Wheel Drive)	In-line	BS IV	Rear, Transverse	Injection	24 litres	Petrol	1652 mm	3164 mm	1750 mm	Hatchback	5.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
5	5	Tata	Nano Genx	Xma	Rs. 3,14,815	624 cc	2.0	2.0	RWD (Rear Wheel Drive)	In-line	BS IV	Rear, Transverse	Injection	24 litres	Petrol	1652 mm	3164 mm	1750 mm	Hatchback	5.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
6	6	Datsun	Redi-Go	D	Rs. 2,79,650	799 cc	3.0	4.0	FWD (Front Wheel Drive)	In-line	BS IV	Front, Transverse	Injection	28 litres	Petrol	1541 mm	3429 mm	1560 mm	Hatchback	5.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
7	7	Datsun	Redi-Go	T	Rs. 3,51,832	799 cc	3.0	4.0	FWD (Front Wheel Drive)	In-line	BS IV	Front, Transverse	Injection	28 litres	Petrol	1541 mm	3429 mm	1560 mm	Hatchback	5.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8	8	Datsun	Redi-Go	A	Rs. 3,33,419	799 cc	3.0	4.0	FWD (Front Wheel Drive)	In-line	BS IV	Front, Transverse	Injection	28 litres	Petrol	1541 mm	3429 mm	1560 mm	Hatchback	5.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
9	9	Datsun	Redi-Go	S	Rs. 3,62,000	799 cc	3.0	4.0	FWD (Front Wheel Drive)	In-line	BS IV	Front, Transverse	Injection	28 litres	Petrol	1541 mm	3429 mm	1560 mm	Hatchback	5.0	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

	make	model	car	variant	body_type	fuel_type	fuel_system	type	drivetrain	displacement	cylinders	mileage	power	torque	fuel_tank	height	length	width	doors	seats	wheelbase	airbags	price
1266	Honda	City	Honda City	V Mt Petrol	Sedan	Petrol	Injection	Manual	FWD (Front Wheel Drive)	1497	4	17.80	117.37	145	40.0	1495.0	4440.0	1695.0	4	5	2600.0	2	14922
1267	Honda	City	Honda City	Vx Mt Petrol	Sedan	Petrol	Injection	Manual	FWD (Front Wheel Drive)	1497	4	17.40	117.37	145	40.0	1495.0	4440.0	1695.0	4	5	2600.0	2	16548
1268	Honda	City	Honda City	Vx Cvt Petrol	Sedan	Petrol	Injection	Automatic	FWD (Front Wheel Drive)	1497	4	18.00	117.37	145	40.0	1495.0	4440.0	1695.0	4	5	2600.0	2	18368
1269	Honda	City	Honda City	Sv Mt Diesel	Sedan	Diesel	Injection	Manual	FWD (Front Wheel Drive)	1498	4	25.60	98.63	200	40.0	1495.0	4440.0	1695.0	4	5	2600.0	2	15554
1270	Honda	City	Honda City	V Mt Diesel	Sedan	Diesel	Injection	Manual	FWD (Front Wheel Drive)	1498	4	25.60	98.63	200	40.0	1495.0	4440.0	1695.0	4	5	2600.0	2	16674
1271	Honda	City	Honda City	Vx Mt Diesel	Sedan	Diesel	Injection	Manual	FWD (Front Wheel Drive)	1498	4	25.10	98.63	200	40.0	1495.0	4440.0	1695.0	4	5	2600.0	2	18228
1272	Honda	City	Honda City	Zx Mt Diesel	Sedan	Diesel	Injection	Manual	FWD (Front Wheel Drive)	1498	4	25.10	98.63	200	40.0	1495.0	4440.0	1695.0	4	5	2600.0	6	19894
1273	Honda	City	Honda City	Zx Cvt Petrol	Sedan	Petrol	Injection	Automatic	FWD (Front Wheel Drive)	1497	4	22.60	117.37	145	40.0	1495.0	4440.0	1695.0	4	5	2600.0	6	20034
1274	Honda	City	Honda City	V Cvt Petrol	Sedan	Petrol	Injection	Automatic	FWD (Front Wheel Drive)	1497	4	17.80	117.37	145	40.0	1495.0	4440.0	1695.0	4	5	2600.0	2	16814
1275	Mitsubishi	Montero	Mitsubishi Montero	3.2 At	SUV	Diesel	Injection	Automatic	AWD (All Wheel Drive)	3200	4	11.56	199.24	441	88.0	1900.0	4900.0	1875.0	5	7	2780.0	6	96075